SoroushVahidi/scidocs huggingface dataset:
Tracking-assisted Weakly Supervised Online Visual Object Segmentation in Unconstrained Videos
(2018)

This paper tackles the task of online video object segmentation with weak supervision, i.e., labeling the target object and background with pixel-level accuracy in unconstrained videos, given only one bounding box information in the first frame. We present a novel tracking-assisted visual object segmentation framework to achieve this. On the one hand, initialized with a given bounding box in the first frame, the auxiliary object tracking module guides the segmentation module frame by frame by providing motion and region information, which is usually missing in semi-supervised methods. Moreover, compared with the unsupervised approach, our approach with such minimum supervision can focus on the target object without bringing unrelated objects into the final results. On the other hand, the video object segmentation module also improves the robustness of the visual object tracking module by pixel-level localization and objectness information. Thus, segmentation and tracking in our framework can mutually help each other in an online manner. To verify the generality and effectiveness of the proposed framework, we evaluate our weakly supervised method on two cross-domain datasets, i.e., the DAVIS and VOT2016 datasets, with the same configuration and parameter setting. Experimental results show the top performance of our method, which is even better than the leading semi-supervised methods. Furthermore, we conduct the extensive ablation study on our approach to investigate the influence of each component and main parameters.
A 77-GHz MMIC power amplifier for automotive radar applications
(2003)

A MMIC 77-GHz two-stage power amplifier (PA) is reported in this letter. This MMIC chip demonstrated a measured small signal gain of over 10 dB from 75 GHz to 80 GHz with 18.5-dBm output power at 1 dB compression. The maximum small signal gain is above 12 dB from 77 to 78 GHz. The saturated output power is better than 21.5 dBm and the maximum power added efficiency is 10% between 75 GHz and 78 GHz. This chip is fabricated using 0.1-/spl mu/m AlGaAs/InGaAs/GaAs PHEMT MMIC process on 4-mil GaAs substrate. The output power performance is the highest among the reported 4-mil MMIC GaAs HEMT PAs at this frequency and therefore it is suitable for the 77-GHz automotive radar systems and related transmitter applications in W-band.
Paralinguistics in speech and language - State-of-the-art and the challenge
(2013)

Paralinguistic analysis is increasingly turning into a mainstream topic in speech and language processing. This article aims to provide a broad overview of the constantly growing field by defining the field, introducing typical applications, presenting exemplary resources, and sharing a unified view of the chain of processing. It then presents the first broader Paralinguistic Challenge organised at INTERSPEECH 2010 by the authors including a historical overview of the Challenge tasks of recognising age, gender, and affect, a summary of methods used by the participants, and their results. In addition, we present the new benchmark obtained by fusion of participants’ predictions and conclude by discussing ten recent and emerging trends in the analysis of paralinguistics in speech and language. © 2012 Elsevier Ltd. All rights reserved.
The Ensembl gene annotation system
(2016)

The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail.Database URL: http://www.ensembl.org/index.html.
LocationSpark: A Distributed In-Memory Data Management System for Big Spatial Data
(2016)

We present LocationSpark, a spatial data processing system built on top of Apache Spark, a widely used distributed data processing system. LocationSpark offers a rich set of spatial query operators, e.g., range search, kNN, spatio-textual operation, spatial-join, and kNN-join. To achieve high performance, LocationSpark employs various spatial indexes for in-memory data, and guarantees that immutable spatial indexes have low overhead with fault tolerance. In addition, we build two new layers over Spark, namely a query scheduler and a query executor. The query scheduler is responsible for mitigating skew in spatial queries, while the query executor selects the best plan based on the indexes and the nature of the spatial queries. Furthermore, to avoid unnecessary network communication overhead when processing overlapped spatial data, We embed an efficient spatial Bloom filter into LocationSpark’s indexes. Finally, LocationSpark tracks frequently accessed spatial data, and dynamically flushes less frequently accessed data into disk. We evaluate our system on real workloads and demonstrate that it achieves an order of magnitude performance gain over a baseline framework.
Deep Gaussian Mixture-Hidden Markov Model for Classification of EEG Signals
(2018)

Electroencephalography (EEG) signals are complex dynamic phenomena that exhibit nonlinear and nonstationary behaviors. These characteristics tend to undermine the reliability of existing hand-crafted EEG features that ignore time-varying information and impair the performances of classification models. In this paper, we propose a novel method that can automatically capture the nonstationary dynamics of EEG signals for diverse classification tasks. It consists of two components. The first component uses an autoregressive-deep variational autoencoder model for automatic feature extraction, and the second component uses a Gaussian mixture-hidden Markov model for EEG classification with the extracted features. We compare the performance of our proposed method and the state-of-the-art methods in two EEG classification tasks, subject, and event classification. Results show that our approach outperforms the others by averages of <inline-formula><tex-math notation="LaTeX">$\text{15}\%\pm \text{6.3}$</tex-math> </inline-formula> (p-value <inline-formula><tex-math notation="LaTeX">$<\text{0.05}$</tex-math></inline-formula>) and <inline-formula><tex-math notation="LaTeX">$\text{22}\%\pm \text{5.7}$</tex-math></inline-formula> (p-value <inline-formula><tex-math notation="LaTeX">$<\text{0.05}$</tex-math></inline-formula>) for subject and event classifications, respectively.
Collaboration with Lean Media: how open-source software succeeds
(2000)

Open-source software, usually created by volunteer programmers dispersed worldwide, now competes with that developed by software firms. This achievement is particularly impressive as open-source programmers rarely meet. They rely heavily on electronic media, which preclude the benefits of face-to-face contact that programmers enjoy within firms. In this paper, we describe findings that address this paradox based on observation, interviews and quantitative analyses of two open-source projects. The findings suggest that spontaneous work coordinated afterward is effective, rational organizational culture helps achieve agreement among members and communications media moderately support spontaneous work. These findings can imply a new model of dispersed collaboration.
Face Detection By Finding The Facial Features And The Angle of Inclination of Tilted Face
(2013)

Face is a popular topic of research in computer vision, image analysis and understanding. This paper proposes a method to detect straight posed face as well as tilted face in colour images. Algorithm first detects skin colour region and then skin region is further processed by finding connected components and holes. Each connected components is tested to extract facial features and Y-value of each holes. If features exist in the connected component then the component is concluded as face. The Y-value of both eyes are compared to find whether the face is straight or tilted. For tilted face, the angle of tilt is determined and the input image is rotated by the angle of tilt to straighten up the face. After straightening the face, the rectangle is drawn to enclose the face. The dimension of drawn rectangle is obtained by using the distance parameter of the line between two eyes.
Quality Attributes of Web Software Applications
(2002)

In only four or five years, the world wide web has changed from a static collection of HTML web pages to a dynamic engine that powers e-commerce, collaborative work, and distribution of information and entertainment. These exciting changes have been fueled by many changes in software technology, the software development process, and how software is deployed. Although the word “heterogeneous” is commonly used to describe web software, we might easily forget to notice in how many ways it can be applied. In fact, the synonymous term “diverse” is more general and familiar, and may be more appropriate. Web software applications use diverse types of hardware, they include a diverse collection of types of implementation languages (including traditional programs, HTML, interpreted scripts, and databases), they are composed of software written in diverse languages, and they are built by collections of people with very diverse sets of skills. Although these changes in how web applications are built are interesting and fascinating, one of the most unique aspects of web software applications is in terms of the needs they must satisfy. Web applications have very high requirements for a number of quality attributes. Some of these quality attributes have been important in other (mostly relatively small) segments of the industry, but some of them are relatively new. This paper discusses some of the unique technological aspects of building web software applications, the unique requirements of quality attributes, and how they can be achieved.
Small-Size Hybrid Loop/Open-Slot Antenna for the LTE Smartphone
(2015)

A small-size hybrid loop/open-slot antenna for the LTE smartphone is presented. The antenna is disposed in a small notch of 7 × 40 mm2 in the system ground plane of the smartphone and has a thickness of 5.8 mm to be capable of embedding within most modern smartphones. The antenna mainly comprises a capacitively fed loop antenna and a ground strip embedded therein to create an open-slot antenna so as to generate additional resonant modes for bandwidth enhancement. The antenna can provide two wide operating bands to cover the LTE low band (698-960 MHz) and the LTE middle/high bands (1710-2690/3400-3800 MHz). In this study, the creation of the open-slot antenna using a ground strip embedded in the ground clearance region for the coupled-fed loop antenna is addressed. The proposed antenna is also fabricated and tested. Both the simulation study and the experimental results are presented.
Word segmentation for the Myanmar language
(2008)

This study reports the development of a Myanmar word segmentation method using Unicode standard encoding. Word segmentation is an essential step prior to natural language processing in the Myanmar language, because a Myanmar text is a string of characters without explicit word boundary delimiters. The proposed method has two phases: syllable segmentation and syllable merging. A rule-based heuristic approach was adopted for syllable segmentation, and a dictionary-based statistical approach for syllable merging. Evaluation of test results showed that the method is very effective for the Myanmar language.
Quasi-Resonant (QR) Controller With Adaptive Switching Frequency Reduction Scheme for Flyback Converter
(2016)

A quasi-resonant (QR) controller with an adaptive frequency reduction scheme has been developed for a flyback converter. While maintaining the valley switching, the QR controller reduces the switching frequency for lighter load by skipping some valleys to reduce the power loss and thereby achieve better light-load efficiency. If the QR controller cannot detect any valley due to the damped oscillation of switch voltage, then the valley switching is given up and the nonvalley switching is employed to keep reducing the switching frequency for lighter load. The proposed QR controller has been implemented in a 0.35-μm 700-V BCDMOS process and applied to a 40-W flyback converter. The power efficiency of the flyback converter is improved by up to 3.0% when the proposed QR controller is employed compared to the one employing the conventional QR controller.
Accelerating Big Data Analytics Using FPGAs
(2015)

Emerging big data analytics applications require a significant amount of server computational power. As chips are hitting power limits, computing systems are moving away from general-purpose designs and toward greater specialization. Hardware acceleration through specialization has received renewed interest in recent years, mainly due to the dark silicon challenge. To address the computing requirements of big data, and based on the benchmarking and characterization results, we envision a data-driven heterogeneous architecture for next generation big data server platforms that leverage the power of field-programmable gate array (FPGA) to build custom accelerators in a Hadoop MapReduce framework. Unlike a full and dedicated implementation of Hadoop MapReduce algorithm on FPGA, we propose the hardware/software (HW/SW) co-design of the algorithm, which trades some speedup at a benefit of less hardware. Considering communication overhead with FPGA and other overheads involved in Hadoop MapReduce environment such as compression and decompression, shuffling and sorting, our experimental results show significant potential for accelerating Hadoop MapReduce machine learning kernels using HW/SW co-design methodology.
The Romance of Learning from Disagreement. The Effect of Cohesiveness and Disagreement on Knowledge Sharing Behavior and Individual Performance Within Teams
(2010)

PURPOSE: The purpose of this study was to explore the effects of disagreement and cohesiveness on knowledge sharing in teams, and on the performance of individual team members. DESIGN/METHODOLOGY/APPROACH: Data were obtained from a survey among 1,354 employees working in 126 teams in 17 organizations. FINDINGS: The results show that cohesiveness has a positive effect on the exchange of advice between team members and on openness for sharing opinions, whereas disagreement has a negative effect on openness for sharing opinions. Furthermore, the exchange of advice in a team has a positive effect on the performance of individual team members and acts as a mediator between cohesiveness and individual performance. IMPLICATIONS: Managers who want to stimulate knowledge sharing processes and performance within work teams may be advised to take measures to prevent disagreement between team members and to enhance team cohesiveness. ORIGINALITY/VALUE: Although some gurus in organizational learning claim that disagreement has a positive effect on group processes such as knowledge sharing and team learning, this study does not support this claim.
Measurement of carotid blood pressure and local pulse wave velocity changes during cuff induced hyperemia
(2017)

We present a prototype design of dual element photoplethysmograph (PPG) probe along with associated measurement system for carotid local pulse wave velocity (PWV) evaluation in a non-invasive and continuous manner. The PPG probe consists of two identical sensing modules placed 23 mm apart. Simultaneously measured blood pulse waveforms from these arterial sites were processed and the pulse transit time delay was resolved using the developed application-specific software. The ability of developed PPG probe and associated measurement system to detect acute changes in carotid local PWV due to blood pressure (BP) variations was experimentally validated by an in-vivo study. Intra-subject carotid BP elevation was achieved by an upper arm cuff based occlusion, which offered a controlled way of local PWV escalation. The elevated carotid BP values were also recorded by a calibrated pressure tonometer prior to the study, and was used as a reference. A significant increment (1.0 – 2.6 m/s) in local PWV was observed and was proportional to the BP increment induced by the occlusive reactive hyperemia. Study results demonstrated the feasibility of real-time signal acquisition and reliable local PWV evaluation under normal and elevated BP conditions using the developed measurement system.
Distributed Compressed Sensing off the Grid
(2015)

This letter investigates the joint recovery of a frequency-sparse signal ensemble sharing a common frequency-sparse component from the collection of their compressed measurements. Unlike conventional arts in compressed sensing, the frequencies follow an off-the-grid formulation and are continuously valued in [0, 1]. As an extension of atomic norm, the concatenated atomic norm minimization approach is proposed to handle the exact recovery of signals, which is reformulated as a computationally tractable semidefinite program. The optimality of the proposed approach is characterized using a dual certificate. Numerical experiments are performed to illustrate the effectiveness of the proposed approach and its advantage over separate recovery.
CallRank: Combating SPIT Using Call Duration, Social Networks and Global Reputation
(2007)

The growing popularity of IP telephony systems has made them attractive targets for spammers. Voice call spam, also known as Spam over Internet Telephony (SPIT), is potentially a more serious problem than email spam because of the real time processing requirements of voice packets. We explore a novel mechanism that uses duration of calls between users to combat SPIT. CallRank, the scheme proposed by us, uses call duration to establish social network linkages and global reputations for callers, based on which call recipients can decide whether the caller is legitimate or not. CallRank has been implemented within a VoIP system simulation and our results show that we are able to achieve a false negative rate of 10% and a false positive rate of 3% even in the presence of a significant fraction of spammers.
Soft gelatin capsules (softgels).
(2010)

It is estimated that more than 40% of new chemical entities (NCEs) coming out of the current drug discovery process have poor biopharmaceutical properties, such as low aqueous solubility and/or permeability. These suboptimal properties pose significant challenges for the oral absorption of the compounds and for the development of orally bioavailable dosage forms. Development of soft gelatin capsule (softgel) dosage form is of growing interest for the oral delivery of poorly water soluble compounds (BCS class II or class IV). The softgel dosage form offers several advantages over other oral dosage forms, such as delivering a liquid matrix designed to solubilize and improve the oral bioavailability of a poorly soluble compound as a unit dose solid dosage form, delivering low and ultra-low doses of a compound, delivering a low melting compound, and minimizing potential generation of dust during manufacturing and thereby improving the safety of production personnel. However, due to the very dynamic nature of the softgel dosage form, its development and stability during its shelf-life are fraught with several challenges. The goal of the current review is to provide an in-depth discussion on the softgel dosage form to formulation scientists who are considering developing softgels for therapeutic compounds.
Fast human segmentation using color and depth
(2017)

Accurate segmentation of humans from live videos is an important problem to be solved in developing immersive video experience. We propose to extract the human segmentation information from color and depth cues in a video using multiple modeling techniques. The prior information from human skeleton data is also fused along with the depth and color models to obtain the final segmentation inside a graph-cut framework. The proposed method runs real time on live videos using single CPU and is shown to be quantitatively outperforming the methods that directly fuse color and depth data.
Multi-Core, Main-Memory Joins: Sort vs. Hash Revisited
(2013)

In this paper we experimentally study the performance of main-memory, parallel, multi-core join algorithms, focusing on sort-merge and (radix-)hash join. The relative performance of these two join approaches have been a topic of discussion for a long time. With the advent of modern multicore architectures, it has been argued that sort-merge join is now a better choice than radix-hash join. This claim is justified based on the width of SIMD instructions (sort-merge outperforms radix-hash join once SIMD is sufficiently wide), and NUMA awareness (sort-merge is superior to hash join in NUMA architectures). We conduct extensive experiments on the original and optimized versions of these algorithms. The experiments show that, contrary to these claims, radixhash join is still clearly superior, and sort-merge approaches to performance of radix only when very large amounts of data are involved. The paper also provides the fastest implementations of these algorithms, and covers many aspects of modern hardware architectures relevant not only for joins but for any parallel data processing operator.
Implementing database operations using SIMD instructions
(2002)

Modern CPUs have instructions that allow basic operations to be performed on several data elements in parallel. These instructions are called SIMD instructions, since they apply a single instruction to multiple data elements. SIMD technology was initially built into commodity processors in order to accelerate the performance of multimedia applications. SIMD instructions provide new opportunities for database engine design and implementation. We study various kinds of operations in a database context, and show how the inner loop of the operations can be accelerated using SIMD instructions. The use of SIMD instructions has two immediate performance benefits: It allows a degree of parallelism, so that many operands can be processed at once. It also often leads to the elimination of conditional branch instructions, reducing branch mispredictions.We consider the most important database operations, including sequential scans, aggregation, index operations, and joins. We present techniques for implementing these using SIMD instructions. We show that there are significant benefits in redesigning traditional query processing algorithms so that they can make better use of SIMD technology. Our study shows that using a SIMD parallelism of four, the CPU time for the new algorithms is from 10% to more than four times less than for the traditional algorithms. Superlinear speedups are obtained as a result of the elimination of branch misprediction effects.
Row-wise parallel predicate evaluation
(2008)

Table scans have become more interesting recently due to greater use of ad-hoc queries and greater availability of multicore, vector-enabled hardware. Table scan performance is limited by value representation, table layout, and processing techniques. In this paper we propose a new layout and processing technique for efficient one-pass predicate evaluation. Starting with a set of rows with a fixed number of bits per column, we append columns to form a set of banks and then pad each bank to a supported machine word length, typically 16, 32, or 64 bits. We then evaluate partial predicates on the columns of each bank, using a novel evaluation strategy that evaluates column level equality, range tests, IN-list predicates, and conjuncts of these predicates, simultaneously on multiple columns within a bank, and on multiple rows within a machine register. This approach outperforms pure column stores, which must evaluate the partial predicates one column at a time. We evaluate and compare the performance and representation overhead of this new approach and several proposed alternatives.